Sparse construction and reconstruction method of array space signals

Abstract

The invention discloses a sparse construction and reconstruction method of array space signals. Due to the fact that the angle of received incident signals changes constantly under the high dynamic condition, enough sampling signals can not be acquired to conduct traditional beam forming. According to the method, a gain test of the array space signals is conducted through the Capon beam forming method based on feature space decomposition, and establishment of a small-snapshot-number sparseness model and OPM reconstruction of the small-snapshot-number sparseness model are conducted based on the compressed sensing theory. The result shows that the method has the advantage of processing undersampled data and achieves estimation on the angle of arrival of the array signals. The method further shows that in the space signal processing field, sparsity makes extraction of related information faster and more effective, so that the signal acquisition cost and the signal processing cost are lowered. By means of the method, expected waveform gain can be obtained in the expected direction of arrival. Compared with a direct sampling method, the method can solve the small snapshot number problem occurring under the high dynamic condition and improve the robustness of a system.

Description

technical field [0001] The invention belongs to the technical field of GNSS engineering safety, is a dynamic beam forming technology, belongs to the field of array signal processing, and in particular relates to a method for sparsely constructing and reconstructing array space signals. Background technique [0002] Array signal processing has a wide range of applications in radar, communication, sonar, speech, and medicine. One of its important research directions is beamforming. Under static conditions, the Capon beamforming method has better resolution and anti-interference performance. However, in a high-dynamic environment, the number of snapshots obtained by the receiver per unit time is much smaller than the number of snapshots obtained under static and low-speed motion conditions. The traditional Capon beam and its improved method cannot form an effective beam gain, so that the desired signal cannot be normal. take over. In 2006, E.Candès, J.Romberg, T.Tao and Dono...

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Problems solved by technology

[0005] Aiming at the problem of low sampling, the present invention studies the influence of sparse reconstruction performance on the estimation of the angle of arrival (DOA) of array signals, and proposes a sparse construction and reconstruction method of array spatial signals. The sparsity of spatial signals refers to the The energy of the space signal is small, and the energy of several space signals is large and the distribution is far apart. A spatial signal distribution state

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